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Performance Prediction of Robust Header Compression version 2 for RTP Audio Streaming Using Linear Regression

机译:使用线性回归的RTP音频流的鲁棒报头压缩版本2的性能预测

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Modern cellular networks utilising the long-term evolution (LTE) and the coming 5G set of standards face an ever-increasing demand for mobile data with low latency from connected devices. Header compression is employed to minimise the overhead for IP-based cellular network traffic, thereby decreasing the overall bandwidth usage, which consequently results in decreased delay for transmissions. In this paper, we evaluate a basic linear function to predict Robust Header Compression version 2's (RFC 5225) RTP compression savings on-the-fly, which will enable the compression to adapt to varying channel conditions dynamically. We find that this approach can achieve more than 90% accuracy for low error rates while being computationally non-demanding. This will aid future compressors to minimise compression overhead, thereby increasing the compression gain even further.
机译:利用长期演进(LTE)和即将到来的5G标准集的现代蜂窝网络面临着对移动数据的不断增长的需求,而连接设备的延迟却很短。采用报头压缩可最大程度地减少基于IP的蜂窝网络流量的开销,从而降低总体带宽使用率,从而减少传输延迟。在本文中,我们评估了一个基本的线性函数,以实时预测稳健的报头压缩版本2(RFC 5225)的RTP压缩节省量,这将使压缩能够动态地适应变化的信道条件。我们发现,这种方法可以实现90%的低错误率精度,同时在计算上不需要。这将有助于未来的压缩机将压缩开销降至最低,从而进一步提高压缩增益。

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